Pandas Profiling Report

Dataset statistics

Number of variables	42
Number of observations	59400
Missing cells	46094
Missing cells (%)	1.8%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	19.5 MiB
Average record size in memory	344.0 B

Variable types

Numeric	10
Categorical	30
Boolean	2

Alerts

`recorded_by` has constant value "GeoData Consultants Ltd"	Constant
`date_recorded` has a high cardinality: 356 distinct values	High cardinality
`funder` has a high cardinality: 1897 distinct values	High cardinality
`installer` has a high cardinality: 2145 distinct values	High cardinality
`wpt_name` has a high cardinality: 37400 distinct values	High cardinality
`subvillage` has a high cardinality: 19287 distinct values	High cardinality
`lga` has a high cardinality: 125 distinct values	High cardinality
`ward` has a high cardinality: 2092 distinct values	High cardinality
`scheme_name` has a high cardinality: 2696 distinct values	High cardinality
`gps_height` is highly correlated with `population` and 1 other fields	High correlation
`population` is highly correlated with `gps_height` and 1 other fields	High correlation
`construction_year` is highly correlated with `gps_height` and 1 other fields	High correlation
`gps_height` is highly correlated with `construction_year`	High correlation
`region_code` is highly correlated with `district_code`	High correlation
`district_code` is highly correlated with `region_code`	High correlation
`construction_year` is highly correlated with `gps_height`	High correlation
`population` is highly correlated with `construction_year`	High correlation
`construction_year` is highly correlated with `population`	High correlation
`quantity_group` is highly correlated with `recorded_by` and 1 other fields	High correlation
`scheme_management` is highly correlated with `recorded_by` and 2 other fields	High correlation
`payment_type` is highly correlated with `recorded_by` and 1 other fields	High correlation
`waterpoint_type_group` is highly correlated with `extraction_type_group` and 4 other fields	High correlation
`source_class` is highly correlated with `recorded_by` and 2 other fields	High correlation
`water_quality` is highly correlated with `recorded_by` and 1 other fields	High correlation
`public_meeting` is highly correlated with `recorded_by`	High correlation
`extraction_type_group` is highly correlated with `waterpoint_type_group` and 4 other fields	High correlation
`basin` is highly correlated with `region` and 1 other fields	High correlation
`region` is highly correlated with `basin` and 1 other fields	High correlation
`status_group` is highly correlated with `recorded_by`	High correlation
`recorded_by` is highly correlated with `quantity_group` and 22 other fields	High correlation
`management_group` is highly correlated with `scheme_management` and 2 other fields	High correlation
`source` is highly correlated with `source_class` and 2 other fields	High correlation
`near_river` is highly correlated with `recorded_by`	High correlation
`management` is highly correlated with `scheme_management` and 2 other fields	High correlation
`quality_group` is highly correlated with `water_quality` and 1 other fields	High correlation
`waterpoint_type` is highly correlated with `waterpoint_type_group` and 4 other fields	High correlation
`permit` is highly correlated with `recorded_by`	High correlation
`source_type` is highly correlated with `source_class` and 2 other fields	High correlation
`extraction_type` is highly correlated with `waterpoint_type_group` and 4 other fields	High correlation
`quantity` is highly correlated with `quantity_group` and 1 other fields	High correlation
`payment` is highly correlated with `payment_type` and 1 other fields	High correlation
`extraction_type_class` is highly correlated with `waterpoint_type_group` and 4 other fields	High correlation
`gps_height` is highly correlated with `latitude` and 3 other fields	High correlation
`longitude` is highly correlated with `latitude` and 5 other fields	High correlation
`latitude` is highly correlated with `gps_height` and 6 other fields	High correlation
`basin` is highly correlated with `gps_height` and 7 other fields	High correlation
`region` is highly correlated with `gps_height` and 17 other fields	High correlation
`region_code` is highly correlated with `longitude` and 4 other fields	High correlation
`district_code` is highly correlated with `latitude` and 2 other fields	High correlation
`scheme_management` is highly correlated with `longitude` and 4 other fields	High correlation
`construction_year` is highly correlated with `gps_height` and 3 other fields	High correlation
`extraction_type` is highly correlated with `basin` and 8 other fields	High correlation
`extraction_type_group` is highly correlated with `region` and 6 other fields	High correlation
`extraction_type_class` is highly correlated with `region` and 8 other fields	High correlation
`management` is highly correlated with `region` and 2 other fields	High correlation
`management_group` is highly correlated with `scheme_management` and 3 other fields	High correlation
`payment` is highly correlated with `region` and 2 other fields	High correlation
`payment_type` is highly correlated with `region` and 2 other fields	High correlation
`water_quality` is highly correlated with `quality_group`	High correlation
`quality_group` is highly correlated with `water_quality`	High correlation
`quantity` is highly correlated with `management_group` and 1 other fields	High correlation
`quantity_group` is highly correlated with `management_group` and 1 other fields	High correlation
`source` is highly correlated with `latitude` and 8 other fields	High correlation
`source_type` is highly correlated with `region` and 7 other fields	High correlation
`source_class` is highly correlated with `extraction_type` and 3 other fields	High correlation
`waterpoint_type` is highly correlated with `region` and 6 other fields	High correlation
`waterpoint_type_group` is highly correlated with `region` and 7 other fields	High correlation
`funder` has 3635 (6.1%) missing values	Missing
`installer` has 3655 (6.2%) missing values	Missing
`public_meeting` has 3334 (5.6%) missing values	Missing
`scheme_management` has 3877 (6.5%) missing values	Missing
`scheme_name` has 28166 (47.4%) missing values	Missing
`permit` has 3056 (5.1%) missing values	Missing
`amount_tsh` is highly skewed (γ1 = 57.80779995)	Skewed
`num_private` is highly skewed (γ1 = 91.93374999)	Skewed
`id` is uniformly distributed	Uniform
`id` has unique values	Unique
`amount_tsh` has 41639 (70.1%) zeros	Zeros
`gps_height` has 20438 (34.4%) zeros	Zeros
`longitude` has 1812 (3.1%) zeros	Zeros
`num_private` has 58643 (98.7%) zeros	Zeros
`population` has 21381 (36.0%) zeros	Zeros
`construction_year` has 20709 (34.9%) zeros	Zeros

Reproduction

Analysis started	2021-11-01 17:26:00.828336
Analysis finished	2021-11-01 17:26:35.361787
Duration	34.53 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

id
Real number (ℝ_≥0)

UNIFORM
UNIQUE

Distinct	59400
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	37115.13177

Minimum	0
Maximum	74247
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	0
5-th percentile	3730.9
Q1	18519.75
median	37061.5
Q3	55656.5
95-th percentile	70564.05
Maximum	74247
Range	74247
Interquartile range (IQR)	37136.75

Descriptive statistics

Standard deviation	21453.12837
Coefficient of variation (CV)	0.5780156866
Kurtosis	-1.201515029
Mean	37115.13177
Median Absolute Deviation (MAD)	18568.5
Skewness	0.00262253035
Sum	2204638827
Variance	460236716.9
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
2047	1	< 0.1%
72310	1	< 0.1%
49805	1	< 0.1%
51852	1	< 0.1%
62091	1	< 0.1%
64138	1	< 0.1%
57993	1	< 0.1%
60040	1	< 0.1%
33413	1	< 0.1%
35460	1	< 0.1%
Other values (59390)	59390	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
4	1	< 0.1%
5	1	< 0.1%
6	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
9	1	< 0.1%

Value	Count	Frequency (%)
74247	1	< 0.1%
74246	1	< 0.1%
74243	1	< 0.1%
74242	1	< 0.1%
74240	1	< 0.1%
74239	1	< 0.1%
74238	1	< 0.1%
74237	1	< 0.1%
74236	1	< 0.1%
74235	1	< 0.1%

amount_tsh
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	98
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	317.6503847

Minimum	0
Maximum	350000
Zeros	41639
Zeros (%)	70.1%
Negative	0
Negative (%)	0.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	20
95-th percentile	1200
Maximum	350000
Range	350000
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	2997.574558
Coefficient of variation (CV)	9.436709989
Kurtosis	4903.543102
Mean	317.6503847
Median Absolute Deviation (MAD)	0
Skewness	57.80779995
Sum	18868432.85
Variance	8985453.232
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	41639	70.1%
500	3102	5.2%
50	2472	4.2%
1000	1488	2.5%
20	1463	2.5%
200	1220	2.1%
100	816	1.4%
10	806	1.4%
30	743	1.3%
2000	704	1.2%
Other values (88)	4947	8.3%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	41639	70.1%
0.2	3	< 0.1%
0.25	1	< 0.1%
1	3	< 0.1%
2	13	< 0.1%
5	376	0.6%
6	190	0.3%
7	69	0.1%
9	1	< 0.1%
10	806	1.4%

Value	Count	Frequency (%)
350000	1	< 0.1%
250000	1	< 0.1%
200000	1	< 0.1%
170000	1	< 0.1%
138000	1	< 0.1%
120000	1	< 0.1%
117000	7	< 0.1%
100000	3	< 0.1%
70000	1	< 0.1%
60000	1	< 0.1%

date_recorded
Categorical

HIGH CARDINALITY

Distinct	356
Distinct (%)	0.6%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

2011-03-15	572
2011-03-17	558
2013-02-03	546
2011-03-14	520
2011-03-16	513
Other values (351)	56691

Length

Max length	10
Median length	10
Mean length	10
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	35 ?
Unique (%)	0.1%

Sample

1st row	2011-03-14
2nd row	2013-03-06
3rd row	2013-02-25
4th row	2013-01-28
5th row	2011-07-13

Common Values

Value	Count	Frequency (%)
2011-03-15	572	1.0%
2011-03-17	558	0.9%
2013-02-03	546	0.9%
2011-03-14	520	0.9%
2011-03-16	513	0.9%
2011-03-18	497	0.8%
2011-03-19	466	0.8%
2013-02-04	464	0.8%
2013-01-29	459	0.8%
2011-03-04	458	0.8%
Other values (346)	54347	91.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
2011-03-15	572	1.0%
2011-03-17	558	0.9%
2013-02-03	546	0.9%
2011-03-14	520	0.9%
2011-03-16	513	0.9%
2011-03-18	497	0.8%
2011-03-19	466	0.8%
2013-02-04	464	0.8%
2013-01-29	459	0.8%
2011-03-04	458	0.8%
Other values (346)	54347	91.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

funder
Categorical

HIGH CARDINALITY
MISSING

Distinct	1897
Distinct (%)	3.4%
Missing	3635
Missing (%)	6.1%
Memory size	928.1 KiB

Government Of Tanzania	9084
Danida	3114
Hesawa	2202
Rwssp	1374
World Bank	1349
Other values (1892)	38642

Length

Max length	30
Median length	6
Mean length	9.929902268
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	974 ?
Unique (%)	1.7%

Sample

1st row	Roman
2nd row	Grumeti
3rd row	Lottery Club
4th row	Unicef
5th row	Action In A

Common Values

Value	Count	Frequency (%)
Government Of Tanzania	9084	15.3%
Danida	3114	5.2%
Hesawa	2202	3.7%
Rwssp	1374	2.3%
World Bank	1349	2.3%
Kkkt	1287	2.2%
World Vision	1246	2.1%
Unicef	1057	1.8%
Tasaf	877	1.5%
District Council	843	1.4%
Other values (1887)	33332	56.1%
(Missing)	3635	6.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
of	9748	10.8%
government	9276	10.3%
tanzania	9172	10.1%
danida	3123	3.5%
world	2789	3.1%
water	2645	2.9%
hesawa	2203	2.4%
bank	1416	1.6%
rwssp	1376	1.5%
kkkt	1370	1.5%
Other values (2065)	47254	52.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

gps_height
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	2428
Distinct (%)	4.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	668.2972391

Minimum	-90
Maximum	2770
Zeros	20438
Zeros (%)	34.4%
Negative	1496
Negative (%)	2.5%
Memory size	928.1 KiB

Quantile statistics

Minimum	-90
5-th percentile	0
Q1	0
median	369
Q3	1319.25
95-th percentile	1797
Maximum	2770
Range	2860
Interquartile range (IQR)	1319.25

Descriptive statistics

Standard deviation	693.1163503
Coefficient of variation (CV)	1.037137833
Kurtosis	-1.292440135
Mean	668.2972391
Median Absolute Deviation (MAD)	369
Skewness	0.462402085
Sum	39696856
Variance	480410.2751
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	20438	34.4%
-15	60	0.1%
-16	55	0.1%
-13	55	0.1%
-20	52	0.1%
1290	52	0.1%
-14	51	0.1%
303	51	0.1%
-18	49	0.1%
-19	47	0.1%
Other values (2418)	38490	64.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-90	1	< 0.1%
-63	2	< 0.1%
-59	1	< 0.1%
-57	1	< 0.1%
-55	1	< 0.1%
-54	1	< 0.1%
-53	1	< 0.1%
-52	2	< 0.1%
-51	2	< 0.1%
-50	5	< 0.1%

Value	Count	Frequency (%)
2770	1	< 0.1%
2628	1	< 0.1%
2627	1	< 0.1%
2626	2	< 0.1%
2623	1	< 0.1%
2614	1	< 0.1%
2585	1	< 0.1%
2576	1	< 0.1%
2569	1	< 0.1%
2568	1	< 0.1%

installer
Categorical

HIGH CARDINALITY
MISSING

Distinct	2145
Distinct (%)	3.8%
Missing	3655
Missing (%)	6.2%
Memory size	928.1 KiB

DWE	17402
Government	1825
RWE	1206
Commu	1060
DANIDA	1050
Other values (2140)	33202

Length

Max length	30
Median length	4
Mean length	6.111202798
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1098 ?
Unique (%)	2.0%

Sample

1st row	Roman
2nd row	GRUMETI
3rd row	World vision
4th row	UNICEF
5th row	Artisan

Common Values

Value	Count	Frequency (%)
DWE	17402	29.3%
Government	1825	3.1%
RWE	1206	2.0%
Commu	1060	1.8%
DANIDA	1050	1.8%
KKKT	898	1.5%
Hesawa	840	1.4%
0	777	1.3%
TCRS	707	1.2%
Central government	622	1.0%
Other values (2135)	29358	49.4%
(Missing)	3655	6.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
dwe	17601	25.8%
government	2778	4.1%
water	1881	2.8%
hesawa	1395	2.0%
rwe	1230	1.8%
district	1216	1.8%
kkkt	1153	1.7%
council	1106	1.6%
commu	1065	1.6%
danida	1051	1.5%
Other values (1976)	37806	55.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

longitude
Real number (ℝ_≥0)

HIGH CORRELATION
ZEROS

Distinct	57516
Distinct (%)	96.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	34.07742669

Minimum	0
Maximum	40.34519307
Zeros	1812
Zeros (%)	3.1%
Negative	0
Negative (%)	0.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	0
5-th percentile	30.04066001
Q1	33.09034738
median	34.90874343
Q3	37.17838657
95-th percentile	39.13323954
Maximum	40.34519307
Range	40.34519307
Interquartile range (IQR)	4.08803919

Descriptive statistics

Standard deviation	6.567431846
Coefficient of variation (CV)	0.1927208854
Kurtosis	19.18703105
Mean	34.07742669
Median Absolute Deviation (MAD)	2.032511095
Skewness	-4.191046455
Sum	2024199.146
Variance	43.13116105
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1812	3.1%
37.54090064	2	< 0.1%
33.01050977	2	< 0.1%
39.09348389	2	< 0.1%
32.9727187	2	< 0.1%
33.00627548	2	< 0.1%
39.10395018	2	< 0.1%
37.54278497	2	< 0.1%
36.80248988	2	< 0.1%
39.09837398	2	< 0.1%
Other values (57506)	57570	96.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1812	3.1%
29.6071219	1	< 0.1%
29.60720109	1	< 0.1%
29.61032056	1	< 0.1%
29.61096482	1	< 0.1%
29.61194674	1	< 0.1%
29.61250689	1	< 0.1%
29.61276296	1	< 0.1%
29.61344309	1	< 0.1%
29.6168718	1	< 0.1%

Value	Count	Frequency (%)
40.34519307	1	< 0.1%
40.34430089	1	< 0.1%
40.32523996	1	< 0.1%
40.32522643	1	< 0.1%
40.32340181	1	< 0.1%
40.32283237	1	< 0.1%
40.32280453	1	< 0.1%
40.3226251	1	< 0.1%
40.32216902	1	< 0.1%
40.32196593	1	< 0.1%

latitude
Real number (ℝ)

HIGH CORRELATION

Distinct	57517
Distinct (%)	96.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-5.70603266

Minimum	-11.64944018
Maximum	-2 × 10^-8
Zeros	0
Zeros (%)	0.0%
Negative	59400
Negative (%)	100.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	-11.64944018
5-th percentile	-10.58554992
Q1	-8.540621305
median	-5.02159665
Q3	-3.32615564
95-th percentile	-1.408872227
Maximum	-2 × 10^-8
Range	11.64944016
Interquartile range (IQR)	5.214465665

Descriptive statistics

Standard deviation	2.946019081
Coefficient of variation (CV)	-0.5162990219
Kurtosis	-1.057616666
Mean	-5.70603266
Median Absolute Deviation (MAD)	2.07002988
Skewness	-0.1520365709
Sum	-338938.34
Variance	8.679028427
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
-2 × 10^-8	1812	3.1%
-6.98584173	2	< 0.1%
-3.79757861	2	< 0.1%
-6.98188419	2	< 0.1%
-7.10462503	2	< 0.1%
-7.05692253	2	< 0.1%
-7.17517443	2	< 0.1%
-6.99073094	2	< 0.1%
-6.9787555	2	< 0.1%
-6.99470401	2	< 0.1%
Other values (57507)	57570	96.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-11.64944018	1	< 0.1%
-11.64837759	1	< 0.1%
-11.58629656	1	< 0.1%
-11.56857679	1	< 0.1%
-11.56680457	1	< 0.1%
-11.56450865	1	< 0.1%
-11.56432357	1	< 0.1%
-11.56231592	1	< 0.1%
-11.56228898	1	< 0.1%
-11.56161898	1	< 0.1%

Value	Count	Frequency (%)
-2 × 10^-8	1812	3.1%
-0.99846435	1	< 0.1%
-0.998916	1	< 0.1%
-0.99901209	1	< 0.1%
-0.99911702	1	< 0.1%
-0.9994692	1	< 0.1%
-0.99950651	1	< 0.1%
-0.99952232	1	< 0.1%
-1.00058519	1	< 0.1%
-1.0015208	1	< 0.1%

wpt_name
Categorical

HIGH CARDINALITY

Distinct	37400
Distinct (%)	63.0%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

none	3563
Shuleni	1748
Zahanati	830
Msikitini	535
Kanisani	323
Other values (37395)	52401

Length

Max length	30
Median length	10
Mean length	10.96210438
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	32928 ?
Unique (%)	55.4%

Sample

1st row	none
2nd row	Zahanati
3rd row	Kwa Mahundi
4th row	Zahanati Ya Nanyumbu
5th row	Shuleni

Common Values

Value	Count	Frequency (%)
none	3563	6.0%
Shuleni	1748	2.9%
Zahanati	830	1.4%
Msikitini	535	0.9%
Kanisani	323	0.5%
Bombani	271	0.5%
Sokoni	260	0.4%
Ofisini	254	0.4%
School	208	0.4%
Shule Ya Msingi	199	0.3%
Other values (37390)	51209	86.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
kwa	21384	19.6%
none	3565	3.3%
mzee	3385	3.1%
shuleni	2123	1.9%
ya	1499	1.4%
shule	1389	1.3%
school	1113	1.0%
primary	1052	1.0%
zahanati	983	0.9%
msingi	870	0.8%
Other values (29461)	71931	65.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

num_private
Real number (ℝ_≥0)

SKEWED
ZEROS

Distinct	65
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.4741414141

Minimum	0
Maximum	1776
Zeros	58643
Zeros (%)	98.7%
Negative	0
Negative (%)	0.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	0
Maximum	1776
Range	1776
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	12.23622981
Coefficient of variation (CV)	25.80713147
Kurtosis	11137.29521
Mean	0.4741414141
Median Absolute Deviation (MAD)	0
Skewness	91.93374999
Sum	28164
Variance	149.72532
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	58643	98.7%
6	81	0.1%
1	73	0.1%
5	46	0.1%
8	46	0.1%
32	40	0.1%
45	36	0.1%
15	35	0.1%
39	30	0.1%
93	28	< 0.1%
Other values (55)	342	0.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	58643	98.7%
1	73	0.1%
2	23	< 0.1%
3	27	< 0.1%
4	20	< 0.1%
5	46	0.1%
6	81	0.1%
7	26	< 0.1%
8	46	0.1%
9	4	< 0.1%

Value	Count	Frequency (%)
1776	1	< 0.1%
1402	1	< 0.1%
755	1	< 0.1%
698	1	< 0.1%
672	1	< 0.1%
668	1	< 0.1%
450	1	< 0.1%
300	1	< 0.1%
280	1	< 0.1%
240	1	< 0.1%

basin
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	9
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

Lake Victoria	10248
Pangani	8940
Rufiji	7976
Internal	7785
Lake Tanganyika	6432
Other values (4)	18019

Length

Max length	23
Median length	10
Mean length	10.8923569
Min length	6

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Lake Nyasa
2nd row	Lake Victoria
3rd row	Pangani
4th row	Ruvuma / Southern Coast
5th row	Lake Victoria

Common Values

Value	Count	Frequency (%)
Lake Victoria	10248	17.3%
Pangani	8940	15.1%
Rufiji	7976	13.4%
Internal	7785	13.1%
Lake Tanganyika	6432	10.8%
Wami / Ruvu	5987	10.1%
Lake Nyasa	5085	8.6%
Ruvuma / Southern Coast	4493	7.6%
Lake Rukwa	2454	4.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
lake	24219	22.2%
	10480	9.6%
victoria	10248	9.4%
pangani	8940	8.2%
rufiji	7976	7.3%
internal	7785	7.1%
tanganyika	6432	5.9%
ruvu	5987	5.5%
wami	5987	5.5%
nyasa	5085	4.7%
Other values (4)	15933	14.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

subvillage
Categorical

HIGH CARDINALITY

Distinct	19287
Distinct (%)	32.7%
Missing	371
Missing (%)	0.6%
Memory size	928.1 KiB

Madukani	508
Shuleni	506
Majengo	502
Kati	373
Mtakuja	262
Other values (19282)	56878

Length

Max length	30
Median length	7
Mean length	7.897592709
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	9424 ?
Unique (%)	16.0%

Sample

1st row	Mnyusi B
2nd row	Nyamara
3rd row	Majengo
4th row	Mahakamani
5th row	Kyanyamisa

Common Values

Value	Count	Frequency (%)
Madukani	508	0.9%
Shuleni	506	0.9%
Majengo	502	0.8%
Kati	373	0.6%
Mtakuja	262	0.4%
Sokoni	232	0.4%
M	187	0.3%
Muungano	172	0.3%
Mbuyuni	164	0.3%
Mlimani	152	0.3%
Other values (19277)	55971	94.2%
(Missing)	371	0.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
a	2387	3.4%
b	2043	2.9%
kati	1902	2.7%
majengo	610	0.9%
wa	600	0.8%
shuleni	593	0.8%
madukani	569	0.8%
mtaa	514	0.7%
juu	403	0.6%
mjini	378	0.5%
Other values (17024)	60795	85.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

region
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	21
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

Iringa	5294
Shinyanga	4982
Mbeya	4639
Kilimanjaro	4379
Morogoro	4006
Other values (16)	36100

Length

Max length	13
Median length	6
Mean length	6.623754209
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Iringa
2nd row	Mara
3rd row	Manyara
4th row	Mtwara
5th row	Kagera

Common Values

Value	Count	Frequency (%)
Iringa	5294	8.9%
Shinyanga	4982	8.4%
Mbeya	4639	7.8%
Kilimanjaro	4379	7.4%
Morogoro	4006	6.7%
Arusha	3350	5.6%
Kagera	3316	5.6%
Mwanza	3102	5.2%
Kigoma	2816	4.7%
Ruvuma	2640	4.4%
Other values (11)	20876	35.1%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
iringa	5294	8.7%
shinyanga	4982	8.2%
mbeya	4639	7.6%
kilimanjaro	4379	7.2%
morogoro	4006	6.6%
arusha	3350	5.5%
kagera	3316	5.4%
mwanza	3102	5.1%
kigoma	2816	4.6%
ruvuma	2640	4.3%
Other values (13)	22486	36.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

region_code
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	27
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	15.29700337

Minimum	1
Maximum	99
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	5
median	12
Q3	17
95-th percentile	60
Maximum	99
Range	98
Interquartile range (IQR)	12

Descriptive statistics

Standard deviation	17.58740634
Coefficient of variation (CV)	1.149728866
Kurtosis	10.28843341
Mean	15.29700337
Median Absolute Deviation (MAD)	6
Skewness	3.17381811
Sum	908642
Variance	309.3168617
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=27)

Value	Count	Frequency (%)
11	5300	8.9%
17	5011	8.4%
12	4639	7.8%
3	4379	7.4%
5	4040	6.8%
18	3324	5.6%
19	3047	5.1%
2	3024	5.1%
16	2816	4.7%
10	2640	4.4%
Other values (17)	21180	35.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	2201	3.7%
2	3024	5.1%
3	4379	7.4%
4	2513	4.2%
5	4040	6.8%
6	1609	2.7%
7	805	1.4%
8	300	0.5%
9	390	0.7%
10	2640	4.4%

Value	Count	Frequency (%)
99	423	0.7%
90	917	1.5%
80	1238	2.1%
60	1025	1.7%
40	1	< 0.1%
24	326	0.5%
21	1583	2.7%
20	1969	3.3%
19	3047	5.1%
18	3324	5.6%

district_code
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	20
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	5.629747475

Minimum	0
Maximum	80
Zeros	23
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	2
median	3
Q3	5
95-th percentile	30
Maximum	80
Range	80
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	9.633648629
Coefficient of variation (CV)	1.711204396
Kurtosis	16.21428363
Mean	5.629747475
Median Absolute Deviation (MAD)	1
Skewness	3.962045299
Sum	334407
Variance	92.80718592
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=20)

Value	Count	Frequency (%)
1	12203	20.5%
2	11173	18.8%
3	9998	16.8%
4	8999	15.1%
5	4356	7.3%
6	4074	6.9%
7	3343	5.6%
8	1043	1.8%
30	995	1.7%
33	874	1.5%
Other values (10)	2342	3.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	23	< 0.1%
1	12203	20.5%
2	11173	18.8%
3	9998	16.8%
4	8999	15.1%
5	4356	7.3%
6	4074	6.9%
7	3343	5.6%
8	1043	1.8%
13	391	0.7%

Value	Count	Frequency (%)
80	12	< 0.1%
67	6	< 0.1%
63	195	0.3%
62	109	0.2%
60	63	0.1%
53	745	1.3%
43	505	0.9%
33	874	1.5%
30	995	1.7%
23	293	0.5%

lga
Categorical

HIGH CARDINALITY

Distinct	125
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

Njombe	2503
Arusha Rural	1252
Moshi Rural	1251
Bariadi	1177
Rungwe	1106
Other values (120)	52111

Length

Max length	16
Median length	6
Mean length	7.416885522
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	Ludewa
2nd row	Serengeti
3rd row	Simanjiro
4th row	Nanyumbu
5th row	Karagwe

Common Values

Value	Count	Frequency (%)
Njombe	2503	4.2%
Arusha Rural	1252	2.1%
Moshi Rural	1251	2.1%
Bariadi	1177	2.0%
Rungwe	1106	1.9%
Kilosa	1094	1.8%
Kasulu	1047	1.8%
Mbozi	1034	1.7%
Meru	1009	1.7%
Bagamoyo	997	1.7%
Other values (115)	46930	79.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
rural	9552	13.5%
njombe	2503	3.5%
urban	1683	2.4%
moshi	1330	1.9%
arusha	1315	1.9%
bariadi	1177	1.7%
singida	1172	1.7%
rungwe	1106	1.6%
kilosa	1094	1.5%
kasulu	1047	1.5%
Other values (106)	48656	68.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

ward
Categorical

HIGH CARDINALITY

Distinct	2092
Distinct (%)	3.5%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

Igosi	307
Imalinyi	252
Siha Kati	232
Mdandu	231
Nduruma	217
Other values (2087)	58161

Length

Max length	23
Median length	7
Mean length	7.505841751
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	30 ?
Unique (%)	0.1%

Sample

1st row	Mundindi
2nd row	Natta
3rd row	Ngorika
4th row	Nanyumbu
5th row	Nyakasimbi

Common Values

Value	Count	Frequency (%)
Igosi	307	0.5%
Imalinyi	252	0.4%
Siha Kati	232	0.4%
Mdandu	231	0.4%
Nduruma	217	0.4%
Mishamo	203	0.3%
Kitunda	203	0.3%
Msindo	201	0.3%
Chalinze	196	0.3%
Maji ya Chai	190	0.3%
Other values (2082)	57168	96.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
mashariki	580	0.9%
urban	540	0.8%
siha	434	0.7%
kusini	393	0.6%
magharibi	362	0.6%
igosi	307	0.5%
masama	303	0.5%
machame	293	0.5%
kati	270	0.4%
imalinyi	252	0.4%
Other values (2106)	61033	94.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

population
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	1049
Distinct (%)	1.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	179.9099832

Minimum	0
Maximum	30500
Zeros	21381
Zeros (%)	36.0%
Negative	0
Negative (%)	0.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	25
Q3	215
95-th percentile	680
Maximum	30500
Range	30500
Interquartile range (IQR)	215

Descriptive statistics

Standard deviation	471.4821757
Coefficient of variation (CV)	2.620655994
Kurtosis	402.2801153
Mean	179.9099832
Median Absolute Deviation (MAD)	25
Skewness	12.66071359
Sum	10686653
Variance	222295.442
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	21381	36.0%
1	7025	11.8%
200	1940	3.3%
150	1892	3.2%
250	1681	2.8%
300	1476	2.5%
100	1146	1.9%
50	1139	1.9%
500	1009	1.7%
350	986	1.7%
Other values (1039)	19725	33.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	21381	36.0%
1	7025	11.8%
2	4	< 0.1%
3	4	< 0.1%
4	13	< 0.1%
5	44	0.1%
6	19	< 0.1%
7	3	< 0.1%
8	23	< 0.1%
9	11	< 0.1%

Value	Count	Frequency (%)
30500	1	< 0.1%
15300	1	< 0.1%
11463	1	< 0.1%
10000	3	< 0.1%
9865	1	< 0.1%
9500	1	< 0.1%
9000	3	< 0.1%
8848	1	< 0.1%
8600	1	< 0.1%
8500	1	< 0.1%

public_meeting
Boolean

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	< 0.1%
Missing	3334
Missing (%)	5.6%
Memory size	928.1 KiB

True	51011
False	5055
(Missing)	3334

Common Values
Chart

Value	Count	Frequency (%)
True	51011	85.9%
False	5055	8.5%
(Missing)	3334	5.6%

recorded_by
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct	1
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

GeoData Consultants Ltd	59400

Length

Max length	23
Median length	23
Mean length	23
Min length	23

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	GeoData Consultants Ltd
2nd row	GeoData Consultants Ltd
3rd row	GeoData Consultants Ltd
4th row	GeoData Consultants Ltd
5th row	GeoData Consultants Ltd

Common Values

Value	Count	Frequency (%)
GeoData Consultants Ltd	59400	100.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
ltd	59400	33.3%
consultants	59400	33.3%
geodata	59400	33.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

scheme_management
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct	12
Distinct (%)	< 0.1%
Missing	3877
Missing (%)	6.5%
Memory size	928.1 KiB

VWC	36793
WUG	5206
Water authority	3153
WUA	2883
Water Board	2748
Other values (7)	4740

Length

Max length	16
Median length	3
Mean length	4.644723808
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	VWC
2nd row	Other
3rd row	VWC
4th row	VWC
5th row	VWC

Common Values

Value	Count	Frequency (%)
VWC	36793	61.9%
WUG	5206	8.8%
Water authority	3153	5.3%
WUA	2883	4.9%
Water Board	2748	4.6%
Parastatal	1680	2.8%
Private operator	1063	1.8%
Company	1061	1.8%
Other	766	1.3%
SWC	97	0.2%
Other values (2)	73	0.1%
(Missing)	3877	6.5%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
vwc	36793	58.9%
water	5901	9.4%
wug	5206	8.3%
authority	3153	5.0%
wua	2883	4.6%
board	2748	4.4%
parastatal	1680	2.7%
operator	1063	1.7%
private	1063	1.7%
company	1061	1.7%
Other values (4)	936	1.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

scheme_name
Categorical

HIGH CARDINALITY
MISSING

Distinct	2696
Distinct (%)	8.6%
Missing	28166
Missing (%)	47.4%
Memory size	928.1 KiB

K	682
None	644
Borehole	546
Chalinze wate	405
M	400
Other values (2691)	28557

Length

Max length	46
Median length	13
Mean length	14.30521227
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	712 ?
Unique (%)	2.3%

Sample

1st row	Roman
2nd row	Nyumba ya mungu pipe scheme
3rd row	Zingibali
4th row	BL Bondeni
5th row	None

Common Values

Value	Count	Frequency (%)
K	682	1.1%
None	644	1.1%
Borehole	546	0.9%
Chalinze wate	405	0.7%
M	400	0.7%
DANIDA	379	0.6%
Government	320	0.5%
Ngana water supplied scheme	270	0.5%
wanging'ombe water supply s	261	0.4%
wanging'ombe supply scheme	234	0.4%
Other values (2686)	27093	45.6%
(Missing)	28166	47.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
water	9770	13.6%
supply	6745	9.4%
scheme	2532	3.5%
wa	2157	3.0%
gravity	1914	2.7%
pipe	1346	1.9%
maji	1343	1.9%
mradi	1097	1.5%
line	1016	1.4%
supplied	877	1.2%
Other values (2506)	43219	60.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

permit
Boolean

HIGH CORRELATION
MISSING

Distinct	2
Distinct (%)	< 0.1%
Missing	3056
Missing (%)	5.1%
Memory size	928.1 KiB

True	38852
False	17492
(Missing)	3056

Common Values
Chart

Value	Count	Frequency (%)
True	38852	65.4%
False	17492	29.4%
(Missing)	3056	5.1%

construction_year
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	55
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1300.652475

Minimum	0
Maximum	2013
Zeros	20709
Zeros (%)	34.9%
Negative	0
Negative (%)	0.0%
Memory size	928.1 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1986
Q3	2004
95-th percentile	2010
Maximum	2013
Range	2013
Interquartile range (IQR)	2004

Descriptive statistics

Standard deviation	951.6205473
Coefficient of variation (CV)	0.7316485885
Kurtosis	-1.596432369
Mean	1300.652475
Median Absolute Deviation (MAD)	22
Skewness	-0.6349277866
Sum	77258757
Variance	905581.6661
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	20709	34.9%
2010	2645	4.5%
2008	2613	4.4%
2009	2533	4.3%
2000	2091	3.5%
2007	1587	2.7%
2006	1471	2.5%
2003	1286	2.2%
2011	1256	2.1%
2004	1123	1.9%
Other values (45)	22086	37.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	20709	34.9%
1960	102	0.2%
1961	21	< 0.1%
1962	30	0.1%
1963	85	0.1%
1964	40	0.1%
1965	19	< 0.1%
1966	17	< 0.1%
1967	88	0.1%
1968	77	0.1%

Value	Count	Frequency (%)
2013	176	0.3%
2012	1084	1.8%
2011	1256	2.1%
2010	2645	4.5%
2009	2533	4.3%
2008	2613	4.4%
2007	1587	2.7%
2006	1471	2.5%
2005	1011	1.7%
2004	1123	1.9%

extraction_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	18
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

gravity	26780
nira/tanira	8154
other	6430
submersible	4764
swn 80	3670
Other values (13)	9602

Length

Max length	25
Median length	7
Mean length	7.719511785
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	gravity
2nd row	gravity
3rd row	gravity
4th row	submersible
5th row	gravity

Common Values

Value	Count	Frequency (%)
gravity	26780	45.1%
nira/tanira	8154	13.7%
other	6430	10.8%
submersible	4764	8.0%
swn 80	3670	6.2%
mono	2865	4.8%
india mark ii	2400	4.0%
afridev	1770	3.0%
ksb	1415	2.4%
other - rope pump	451	0.8%
Other values (8)	701	1.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
gravity	26780	38.1%
nira/tanira	8154	11.6%
other	7197	10.2%
submersible	4764	6.8%
swn	3899	5.5%
80	3670	5.2%
mono	2865	4.1%
india	2498	3.6%
mark	2498	3.6%
ii	2400	3.4%
Other values (13)	5640	8.0%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

extraction_type_group
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	13
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

gravity	26780
nira/tanira	8154
other	6430
submersible	6179
swn 80	3670
Other values (8)	8187

Length

Max length	15
Median length	7
Mean length	7.880538721
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	gravity
2nd row	gravity
3rd row	gravity
4th row	submersible
5th row	gravity

Common Values

Value	Count	Frequency (%)
gravity	26780	45.1%
nira/tanira	8154	13.7%
other	6430	10.8%
submersible	6179	10.4%
swn 80	3670	6.2%
mono	2865	4.8%
india mark ii	2400	4.0%
afridev	1770	3.0%
rope pump	451	0.8%
other handpump	364	0.6%
Other values (3)	337	0.6%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
gravity	26780	38.8%
nira/tanira	8154	11.8%
other	6916	10.0%
submersible	6179	9.0%
swn	3670	5.3%
80	3670	5.3%
mono	2865	4.2%
india	2498	3.6%
mark	2498	3.6%
ii	2400	3.5%
Other values (7)	3373	4.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

extraction_type_class
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

gravity	26780
handpump	16456
other	6430
submersible	6179
motorpump	2987
Other values (2)	568

Length

Max length	12
Median length	7
Mean length	7.602239057
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	gravity
2nd row	gravity
3rd row	gravity
4th row	submersible
5th row	gravity

Common Values

Value	Count	Frequency (%)
gravity	26780	45.1%
handpump	16456	27.7%
other	6430	10.8%
submersible	6179	10.4%
motorpump	2987	5.0%
rope pump	451	0.8%
wind-powered	117	0.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
gravity	26780	44.7%
handpump	16456	27.5%
other	6430	10.7%
submersible	6179	10.3%
motorpump	2987	5.0%
pump	451	0.8%
rope	451	0.8%
wind-powered	117	0.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

management
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	12
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

vwc	40507
wug	6515
water board	2933
wua	2535
private operator	1971
Other values (7)	4939

Length

Max length	16
Median length	3
Mean length	4.350639731
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	vwc
2nd row	wug
3rd row	vwc
4th row	vwc
5th row	other

Common Values

Value	Count	Frequency (%)
vwc	40507	68.2%
wug	6515	11.0%
water board	2933	4.9%
wua	2535	4.3%
private operator	1971	3.3%
parastatal	1768	3.0%
water authority	904	1.5%
other	844	1.4%
company	685	1.2%
unknown	561	0.9%
Other values (2)	177	0.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
vwc	40507	61.9%
wug	6515	10.0%
water	3837	5.9%
board	2933	4.5%
wua	2535	3.9%
operator	1971	3.0%
private	1971	3.0%
parastatal	1768	2.7%
other	943	1.4%
authority	904	1.4%
Other values (5)	1522	2.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

management_group
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

user-group	52490
commercial	3638
parastatal	1768
other	943
unknown	561

Length

Max length	10
Median length	10
Mean length	9.892289562
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	user-group
2nd row	user-group
3rd row	user-group
4th row	user-group
5th row	other

Common Values

Value	Count	Frequency (%)
user-group	52490	88.4%
commercial	3638	6.1%
parastatal	1768	3.0%
other	943	1.6%
unknown	561	0.9%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
user-group	52490	88.4%
commercial	3638	6.1%
parastatal	1768	3.0%
other	943	1.6%
unknown	561	0.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

payment
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

never pay	25348
pay per bucket	8985
pay monthly	8300
unknown	8157
pay when scheme fails	3914
Other values (2)	4696

Length

Max length	21
Median length	9
Mean length	10.66479798
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	pay annually
2nd row	never pay
3rd row	pay per bucket
4th row	never pay
5th row	never pay

Common Values

Value	Count	Frequency (%)
never pay	25348	42.7%
pay per bucket	8985	15.1%
pay monthly	8300	14.0%
unknown	8157	13.7%
pay when scheme fails	3914	6.6%
pay annually	3642	6.1%
other	1054	1.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
pay	50189	39.7%
never	25348	20.1%
bucket	8985	7.1%
per	8985	7.1%
monthly	8300	6.6%
unknown	8157	6.5%
fails	3914	3.1%
scheme	3914	3.1%
when	3914	3.1%
annually	3642	2.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

payment_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

never pay	25348
per bucket	8985
monthly	8300
unknown	8157
on failure	3914
Other values (2)	4696

Length

Max length	10
Median length	9
Mean length	8.530757576
Min length	5

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	annually
2nd row	never pay
3rd row	per bucket
4th row	never pay
5th row	never pay

Common Values

Value	Count	Frequency (%)
never pay	25348	42.7%
per bucket	8985	15.1%
monthly	8300	14.0%
unknown	8157	13.7%
on failure	3914	6.6%
annually	3642	6.1%
other	1054	1.8%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
pay	25348	26.0%
never	25348	26.0%
bucket	8985	9.2%
per	8985	9.2%
monthly	8300	8.5%
unknown	8157	8.4%
failure	3914	4.0%
on	3914	4.0%
annually	3642	3.7%
other	1054	1.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

water_quality
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

soft	50818
salty	4856
unknown	1876
milky	804
coloured	490
Other values (3)	556

Length

Max length	18
Median length	4
Mean length	4.303282828
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	soft
2nd row	soft
3rd row	soft
4th row	soft
5th row	soft

Common Values

Value	Count	Frequency (%)
soft	50818	85.6%
salty	4856	8.2%
unknown	1876	3.2%
milky	804	1.4%
coloured	490	0.8%
salty abandoned	339	0.6%
fluoride	200	0.3%
fluoride abandoned	17	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
soft	50818	85.0%
salty	5195	8.7%
unknown	1876	3.1%
milky	804	1.3%
coloured	490	0.8%
abandoned	356	0.6%
fluoride	217	0.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

quality_group
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

good	50818
salty	5195
unknown	1876
milky	804
colored	490

Length

Max length	8
Median length	4
Mean length	4.23510101
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	good
2nd row	good
3rd row	good
4th row	good
5th row	good

Common Values

Value	Count	Frequency (%)
good	50818	85.6%
salty	5195	8.7%
unknown	1876	3.2%
milky	804	1.4%
colored	490	0.8%
fluoride	217	0.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
good	50818	85.6%
salty	5195	8.7%
unknown	1876	3.2%
milky	804	1.4%
colored	490	0.8%
fluoride	217	0.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

quantity
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

enough	33186
insufficient	15129
dry	6246
seasonal	4050
unknown	789

Length

Max length	12
Median length	6
Mean length	7.362373737
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	enough
2nd row	insufficient
3rd row	enough
4th row	dry
5th row	seasonal

Common Values

Value	Count	Frequency (%)
enough	33186	55.9%
insufficient	15129	25.5%
dry	6246	10.5%
seasonal	4050	6.8%
unknown	789	1.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
enough	33186	55.9%
insufficient	15129	25.5%
dry	6246	10.5%
seasonal	4050	6.8%
unknown	789	1.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

quantity_group
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

enough	33186
insufficient	15129
dry	6246
seasonal	4050
unknown	789

Length

Max length	12
Median length	6
Mean length	7.362373737
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	enough
2nd row	insufficient
3rd row	enough
4th row	dry
5th row	seasonal

Common Values

Value	Count	Frequency (%)
enough	33186	55.9%
insufficient	15129	25.5%
dry	6246	10.5%
seasonal	4050	6.8%
unknown	789	1.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
enough	33186	55.9%
insufficient	15129	25.5%
dry	6246	10.5%
seasonal	4050	6.8%
unknown	789	1.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

source
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	10
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

spring	17021
shallow well	16824
machine dbh	11075
river	9612
rainwater harvesting	2295
Other values (5)	2573

Length

Max length	20
Median length	11
Mean length	8.978804714
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	spring
2nd row	rainwater harvesting
3rd row	dam
4th row	machine dbh
5th row	rainwater harvesting

Common Values

Value	Count	Frequency (%)
spring	17021	28.7%
shallow well	16824	28.3%
machine dbh	11075	18.6%
river	9612	16.2%
rainwater harvesting	2295	3.9%
hand dtw	874	1.5%
lake	765	1.3%
dam	656	1.1%
other	212	0.4%
unknown	66	0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
spring	17021	18.8%
well	16824	18.6%
shallow	16824	18.6%
dbh	11075	12.2%
machine	11075	12.2%
river	9612	10.6%
harvesting	2295	2.5%
rainwater	2295	2.5%
dtw	874	1.0%
hand	874	1.0%
Other values (4)	1699	1.9%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

source_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

spring	17021
shallow well	16824
borehole	11949
river/lake	10377
rainwater harvesting	2295
Other values (2)	934

Length

Max length	20
Median length	8
Mean length	9.303602694
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	spring
2nd row	rainwater harvesting
3rd row	dam
4th row	borehole
5th row	rainwater harvesting

Common Values

Value	Count	Frequency (%)
spring	17021	28.7%
shallow well	16824	28.3%
borehole	11949	20.1%
river/lake	10377	17.5%
rainwater harvesting	2295	3.9%
dam	656	1.1%
other	278	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
spring	17021	21.7%
well	16824	21.4%
shallow	16824	21.4%
borehole	11949	15.2%
river/lake	10377	13.2%
harvesting	2295	2.9%
rainwater	2295	2.9%
dam	656	0.8%
other	278	0.4%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

source_class
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

groundwater	45794
surface	13328
unknown	278

Length

Max length	11
Median length	11
Mean length	10.08377104
Min length	7

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	groundwater
2nd row	surface
3rd row	surface
4th row	groundwater
5th row	surface

Common Values

Value	Count	Frequency (%)
groundwater	45794	77.1%
surface	13328	22.4%
unknown	278	0.5%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
groundwater	45794	77.1%
surface	13328	22.4%
unknown	278	0.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

waterpoint_type
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

communal standpipe	28522
hand pump	17488
other	6380
communal standpipe multiple	6103
improved spring	784
Other values (2)	123

Length

Max length	27
Median length	18
Mean length	14.82757576
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	communal standpipe
2nd row	communal standpipe
3rd row	communal standpipe multiple
4th row	communal standpipe multiple
5th row	communal standpipe

Common Values

Value	Count	Frequency (%)
communal standpipe	28522	48.0%
hand pump	17488	29.4%
other	6380	10.7%
communal standpipe multiple	6103	10.3%
improved spring	784	1.3%
cattle trough	116	0.2%
dam	7	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
standpipe	34625	29.2%
communal	34625	29.2%
pump	17488	14.8%
hand	17488	14.8%
other	6380	5.4%
multiple	6103	5.1%
spring	784	0.7%
improved	784	0.7%
trough	116	0.1%
cattle	116	0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

waterpoint_type_group
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

communal standpipe	34625
hand pump	17488
other	6380
improved spring	784
cattle trough	116

Length

Max length	18
Median length	18
Mean length	13.90287879
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	communal standpipe
2nd row	communal standpipe
3rd row	communal standpipe
4th row	communal standpipe
5th row	communal standpipe

Common Values

Value	Count	Frequency (%)
communal standpipe	34625	58.3%
hand pump	17488	29.4%
other	6380	10.7%
improved spring	784	1.3%
cattle trough	116	0.2%
dam	7	< 0.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
standpipe	34625	30.8%
communal	34625	30.8%
pump	17488	15.6%
hand	17488	15.6%
other	6380	5.7%
spring	784	0.7%
improved	784	0.7%
trough	116	0.1%
cattle	116	0.1%
dam	7	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

status_group
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

functional	32259
non functional	22824
functional needs repair	4317

Length

Max length	23
Median length	10
Mean length	12.48176768
Min length	10

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	functional
2nd row	functional
3rd row	functional
4th row	non functional
5th row	functional

Common Values

Value	Count	Frequency (%)
functional	32259	54.3%
non functional	22824	38.4%
functional needs repair	4317	7.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
functional	59400	65.4%
non	22824	25.1%
repair	4317	4.8%
needs	4317	4.8%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

near_river
Categorical

HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	928.1 KiB

1.0	35481
0.0	23919

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	1.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	35481	59.7%
0.0	23919	40.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
1.0	35481	59.7%
0.0	23919	40.3%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	id	amount_tsh	date_recorded	funder	gps_height	installer	longitude	latitude	wpt_name	basin	subvillage	region	region_code	district_code	lga	ward	population	public_meeting	recorded_by	scheme_management	scheme_name	permit	construction_year	extraction_type	extraction_type_group	extraction_type_class	management	management_group	payment	payment_type	water_quality	quality_group	quantity	quantity_group	source	source_type	source_class	waterpoint_type	waterpoint_type_group	status_group	near_river
0	69572	6000.0	2011-03-14	Roman	1390	Roman	34.938093	-9.856322	none	Lake Nyasa	Mnyusi B	Iringa	11	5	Ludewa	Mundindi	109	True	GeoData Consultants Ltd	VWC	Roman	False	1999	gravity	gravity	gravity	vwc	user-group	pay annually	annually	soft	good	enough	enough	spring	spring	groundwater	communal standpipe	communal standpipe	functional	0.0
1	8776	0.0	2013-03-06	Grumeti	1399	GRUMETI	34.698766	-2.147466	Zahanati	Lake Victoria	Nyamara	Mara	20	2	Serengeti	Natta	280	NaN	GeoData Consultants Ltd	Other	NaN	True	2010	gravity	gravity	gravity	wug	user-group	never pay	never pay	soft	good	insufficient	insufficient	rainwater harvesting	rainwater harvesting	surface	communal standpipe	communal standpipe	functional	1.0
2	34310	25.0	2013-02-25	Lottery Club	686	World vision	37.460664	-3.821329	Kwa Mahundi	Pangani	Majengo	Manyara	21	4	Simanjiro	Ngorika	250	True	GeoData Consultants Ltd	VWC	Nyumba ya mungu pipe scheme	True	2009	gravity	gravity	gravity	vwc	user-group	pay per bucket	per bucket	soft	good	enough	enough	dam	dam	surface	communal standpipe multiple	communal standpipe	functional	1.0
3	67743	0.0	2013-01-28	Unicef	263	UNICEF	38.486161	-11.155298	Zahanati Ya Nanyumbu	Ruvuma / Southern Coast	Mahakamani	Mtwara	90	63	Nanyumbu	Nanyumbu	58	True	GeoData Consultants Ltd	VWC	NaN	True	1986	submersible	submersible	submersible	vwc	user-group	never pay	never pay	soft	good	dry	dry	machine dbh	borehole	groundwater	communal standpipe multiple	communal standpipe	non functional	0.0
4	19728	0.0	2011-07-13	Action In A	0	Artisan	31.130847	-1.825359	Shuleni	Lake Victoria	Kyanyamisa	Kagera	18	1	Karagwe	Nyakasimbi	0	True	GeoData Consultants Ltd	NaN	NaN	True	0	gravity	gravity	gravity	other	other	never pay	never pay	soft	good	seasonal	seasonal	rainwater harvesting	rainwater harvesting	surface	communal standpipe	communal standpipe	functional	1.0
5	9944	20.0	2011-03-13	Mkinga Distric Coun	0	DWE	39.172796	-4.765587	Tajiri	Pangani	Moa/Mwereme	Tanga	4	8	Mkinga	Moa	1	True	GeoData Consultants Ltd	VWC	Zingibali	True	2009	submersible	submersible	submersible	vwc	user-group	pay per bucket	per bucket	salty	salty	enough	enough	other	other	unknown	communal standpipe multiple	communal standpipe	functional	1.0
6	19816	0.0	2012-10-01	Dwsp	0	DWSP	33.362410	-3.766365	Kwa Ngomho	Internal	Ishinabulandi	Shinyanga	17	3	Shinyanga Rural	Samuye	0	True	GeoData Consultants Ltd	VWC	NaN	True	0	swn 80	swn 80	handpump	vwc	user-group	never pay	never pay	soft	good	enough	enough	machine dbh	borehole	groundwater	hand pump	hand pump	non functional	1.0
7	54551	0.0	2012-10-09	Rwssp	0	DWE	32.620617	-4.226198	Tushirikiane	Lake Tanganyika	Nyawishi Center	Shinyanga	17	3	Kahama	Chambo	0	True	GeoData Consultants Ltd	NaN	NaN	True	0	nira/tanira	nira/tanira	handpump	wug	user-group	unknown	unknown	milky	milky	enough	enough	shallow well	shallow well	groundwater	hand pump	hand pump	non functional	0.0
8	53934	0.0	2012-11-03	Wateraid	0	Water Aid	32.711100	-5.146712	Kwa Ramadhan Musa	Lake Tanganyika	Imalauduki	Tabora	14	6	Tabora Urban	Itetemia	0	True	GeoData Consultants Ltd	VWC	NaN	True	0	india mark ii	india mark ii	handpump	vwc	user-group	never pay	never pay	salty	salty	seasonal	seasonal	machine dbh	borehole	groundwater	hand pump	hand pump	non functional	0.0
9	46144	0.0	2011-08-03	Isingiro Ho	0	Artisan	30.626991	-1.257051	Kwapeto	Lake Victoria	Mkonomre	Kagera	18	1	Karagwe	Kaisho	0	True	GeoData Consultants Ltd	NaN	NaN	True	0	nira/tanira	nira/tanira	handpump	vwc	user-group	never pay	never pay	soft	good	enough	enough	shallow well	shallow well	groundwater	hand pump	hand pump	functional	0.0

Last rows

	id	amount_tsh	date_recorded	funder	gps_height	installer	longitude	latitude	wpt_name	basin	subvillage	region	region_code	district_code	lga	ward	population	public_meeting	recorded_by	scheme_management	scheme_name	permit	construction_year	extraction_type	extraction_type_group	extraction_type_class	management	management_group	payment	payment_type	water_quality	quality_group	quantity	quantity_group	source	source_type	source_class	waterpoint_type	waterpoint_type_group	status_group	near_river
59390	13677	0.0	2011-08-04	Rudep	1715	DWE	31.370848	-8.258160	Kwa Mzee Atanas	Lake Tanganyika	Kitonto	Rukwa	15	2	Sumbawanga Rural	Mkowe	150	True	GeoData Consultants Ltd	VWC	NaN	False	1991	swn 80	swn 80	handpump	vwc	user-group	never pay	never pay	soft	good	insufficient	insufficient	machine dbh	borehole	groundwater	hand pump	hand pump	functional	1.0
59391	44885	0.0	2013-08-03	Government Of Tanzania	540	Government	38.044070	-4.272218	Kwa	Pangani	Maore Kati	Kilimanjaro	3	3	Same	Maore	210	True	GeoData Consultants Ltd	Water authority	Hingilili	True	1967	gravity	gravity	gravity	vwc	user-group	never pay	never pay	soft	good	enough	enough	river	river/lake	surface	communal standpipe	communal standpipe	non functional	1.0
59392	40607	0.0	2011-04-15	Government Of Tanzania	0	Government	33.009440	-8.520888	Benard Charles	Lake Rukwa	Mbuyuni A	Mbeya	12	1	Chunya	Mbuyuni	0	True	GeoData Consultants Ltd	VWC	NaN	True	0	gravity	gravity	gravity	vwc	user-group	never pay	never pay	soft	good	enough	enough	spring	spring	groundwater	communal standpipe	communal standpipe	non functional	0.0
59393	48348	0.0	2012-10-27	Private	0	Private	33.866852	-4.287410	Kwa Peter	Internal	Masanga	Tabora	14	2	Igunga	Igunga	0	False	GeoData Consultants Ltd	Water authority	NaN	False	0	gravity	gravity	gravity	private operator	commercial	pay per bucket	per bucket	soft	good	insufficient	insufficient	dam	dam	surface	other	other	functional	0.0
59394	11164	500.0	2011-03-09	World Bank	351	ML appro	37.634053	-6.124830	Chimeredya	Wami / Ruvu	Komstari	Morogoro	5	6	Mvomero	Diongoya	89	True	GeoData Consultants Ltd	VWC	NaN	True	2007	submersible	submersible	submersible	vwc	user-group	pay monthly	monthly	soft	good	enough	enough	machine dbh	borehole	groundwater	communal standpipe	communal standpipe	non functional	0.0
59395	60739	10.0	2013-05-03	Germany Republi	1210	CES	37.169807	-3.253847	Area Three Namba 27	Pangani	Kiduruni	Kilimanjaro	3	5	Hai	Masama Magharibi	125	True	GeoData Consultants Ltd	Water Board	Losaa Kia water supply	True	1999	gravity	gravity	gravity	water board	user-group	pay per bucket	per bucket	soft	good	enough	enough	spring	spring	groundwater	communal standpipe	communal standpipe	functional	0.0
59396	27263	4700.0	2011-05-07	Cefa-njombe	1212	Cefa	35.249991	-9.070629	Kwa Yahona Kuvala	Rufiji	Igumbilo	Iringa	11	4	Njombe	Ikondo	56	True	GeoData Consultants Ltd	VWC	Ikondo electrical water sch	True	1996	gravity	gravity	gravity	vwc	user-group	pay annually	annually	soft	good	enough	enough	river	river/lake	surface	communal standpipe	communal standpipe	functional	1.0
59397	37057	0.0	2011-04-11	NaN	0	NaN	34.017087	-8.750434	Mashine	Rufiji	Madungulu	Mbeya	12	7	Mbarali	Chimala	0	True	GeoData Consultants Ltd	VWC	NaN	False	0	swn 80	swn 80	handpump	vwc	user-group	pay monthly	monthly	fluoride	fluoride	enough	enough	machine dbh	borehole	groundwater	hand pump	hand pump	functional	1.0
59398	31282	0.0	2011-03-08	Malec	0	Musa	35.861315	-6.378573	Mshoro	Rufiji	Mwinyi	Dodoma	1	4	Chamwino	Mvumi Makulu	0	True	GeoData Consultants Ltd	VWC	NaN	True	0	nira/tanira	nira/tanira	handpump	vwc	user-group	never pay	never pay	soft	good	insufficient	insufficient	shallow well	shallow well	groundwater	hand pump	hand pump	functional	0.0
59399	26348	0.0	2011-03-23	World Bank	191	World	38.104048	-6.747464	Kwa Mzee Lugawa	Wami / Ruvu	Kikatanyemba	Morogoro	5	2	Morogoro Rural	Ngerengere	150	True	GeoData Consultants Ltd	VWC	NaN	True	2002	nira/tanira	nira/tanira	handpump	vwc	user-group	pay when scheme fails	on failure	salty	salty	enough	enough	shallow well	shallow well	groundwater	hand pump	hand pump	functional	1.0

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category